Lactation stage, parity, and infection affecting somatic cells, electrical conductivity, and serum albumin in milk

Toll like receptor 4 (TLR4) gene polymorphism and its association with somatic cell score and milk production traits in Indian dromedary camels

Our study aimed to explore the genetic variation in the Toll-like receptor 4 (TLR4) gene and establish its association with somatic cell score (SCS) and milk production traits in four Indian camel breeds namely Bikaneri, Kachchhi, Jaisalmeri and Mewari. TLR4 gene fragment of 573 bp spanning 5' UTR, exon-1 and partial intron-1 region was amplified and genotyped using the PCR-sequence based typing method. Only one SNP located at position C472T was identified. Genotyping revealed two alleles (C and T) and three genotypes: CC, CT and TT. The genotype frequencies for CC, CT and TT were 0.116, 0.326 and 0.558 and allele frequencies for C and T alleles were 0.279 and 0.721, respectively. Association study inferred that the effect of genotype on SCS, lactation yield (LY) and peak yield (PY) was non-significant however heterozygote (CT) genotypes recorded lower SCS and higher LY and PY. It can be concluded that the TLR4 gene possesses limited genetic variation, depicting polymorphism at a single locus in Indian camel breeds with a predominance of the TT genotype. The association study indicated that heterozygote animals possess better udder health and production performance, the statistical significance of which needs to be established using a large data set.

Does Keeping Cows for More Lactations Affect the Composition and Technological Properties of the Milk?

This study investigated differences in the raw milk composition and technological properties between cows with different numbers of lactations. In total, 12 commercial herds were visited within a period of 12 weeks. On each farm, milk samples from five young cows (lactations 1-2) and five older cows (lactation ≥ 3) were collected. For each farm, milk samples from the young cows and the older cows, respectively, were pooled. The pooled milk samples were analyzed for gross composition and technological properties. Using principal component analysis (PCA) to assess the overall variation in milk quality attributes and the potential clustering of milk from young cows and older cows, respectively, an effect of breed, but no clear effect of lactation number, was observed. In contrast, one-way ANOVA showed higher plasmin activity (p = 0.002) in pooled milk from the older cows, whereas plasminogen-derived activity (p = 0.001) and total proteolysis (p = 0.029) were higher in milk from the young cows. Likewise, orthogonal projections to latent structure discriminant analysis (OPLS-DA) showed higher plasmin activity in milk from older cows, whereas younger cows had higher plasminogen-related activity and higher total proteolysis. To conclude, except for plasmin and plasminogen-related activities, there were no major differences in the composition and technological properties between milk from older cows and young cows.

Physicochemical, Microbiological and Technological Properties of Red Deer (Cervus elaphus) Milk during Lactation

Simple Summary

Milk from red deer is richer in fat and proteins than that of cow or other ruminants. The semi-captive breeding of this species has traditionally focused on meat, velvet or hunting purposes, but recent studies suggested that the high level of nutrients, the promising content of bioactive peptides and the better digestibility than that of milk from other species could open innovative alternatives for the dairy industry. As for other non-commercial mammalian species that are gaining technological interest for the elaboration of dairy products, it is necessary to understand the aptitude and performance of milk from red deer to be used for the production of cheese, fermented milks or other products. Our study aims to assess some chemical, physical, microbiological and technological properties of red deer milk during a lactation period of 18 weeks. The results show that milk from this species is similar to that of other ruminant species whose milk is commercialized. In addition, our results indicate the best period to industrialize the milk during lactation. To the best of our knowledge, this is the first study to explore the benefits of using red deer milk with a technological approach.

Abstract

This study describes chemical, physical, microbiological and technological characteristics of red deer milk and the effect of lactation on these parameters in order to know their potential aptitude to elaborate dairy products. During 18 weeks, milk from five hinds was monitored for composition, bacteriology, somatic cell count (SCC), physical properties and rennet coagulation. Mean values (g/100 g) for fat, protein, lactose and dry matter were 10.4, 7.1, 4.3 and 24.2, respectively, and for urea, 265 mg/100 mL. Except for lactose, a significant increase in these components was observed (p < 0.01) as lactation progressed. The average values for bacteriology and SCC were 5.3 log cfu/mL and 4.7 log cells/mL, respectively. Regarding physical properties, conductivity (mean: 2.8 ms/cm), viscosity (3.1 Cp), coordinates L* (89.9) and a* (−3.1) and milk fat globule diameter (D_4,3: 6.1 µm) increased along with lactation while density (1.038 g/mL) decreased (p < 0.01). The pH (6.7), acidity (22.9° Dornic), coordinate b* (8.4) and ethanol stability (66.6% v/v) were stable during the study period. The stage of lactation also has a significant impact on milk coagulation properties and mean curd yield was 3.29 g/10 mL. These results suggest that red deer milk could be a potential innovative source of milk for the dairy industry.

Factors associated with milking-to-milking variability in somatic cell counts from healthy cows in an automatic milking system

Fully automated on-line analysis equipment is available for analysis of somatic cell count (SCC) at every milking in automatic milking systems. In addition to results from on-line cell counters (OCC), an array of additional cow-level and quarter-level factors considered important for udder health are recorded in these systems. However, the amount of variability in SCC that can be explained by available data is unknown, and so is the proportion of the variability that may be due to physiological or normal variability. Our aim was to increase our knowledge on OCC as an indicator for disturbances in udder health by assessing the variability in OCC in cows free from clinical mastitis. The first objective was to evaluate how much of the variability in OCC could be explained by different potential sources of variability, including intramammary infection (IMI) status (assessed by bacterial culture of quarter milk samples). The second objective was to evaluate the repeatability of the OCC sensor used in our study and the agreement between OCC values and SCC measured in a dairy herd improvement (DHI) laboratory. A longitudinal study was performed in the research herd of the Norwegian University of Life Sciences from January 5th 2016 to May 22nd 2017. Data from 62,471 milkings from 173 lactations in 129 cows were analyzed. We used ln-transformed OCC values (in 1000 cells/ml) as the outcome (lnOCC) in linear mixed models, with random intercepts at cow-level and lactation-level within cow. We were able to explain 15.0% of the variability in lnOCC with the following fixed effects: lactation stage, parity, milk yield, OCC in residual milk from the previous milking, inter-quarter difference between the highest and lowest conductivity, season, IMI status, and genetic lineage. When including the random intercepts, the degree of explanation was 55.2%. The individual variables explained only a small part of the total variability in lnOCC. We concluded that physiological or normal variability is probably responsible for a large part of the overall variability in OCC in cows without clinical mastitis. This is important to consider when using OCC data for research purposes or in decision-support tools. Sensor repeatability was evaluated by analyzing milk from the same sample multiple times. The coefficient of variation was 0.11 at an OCC level relevant for detection of subclinical mastitis. The agreement study showed a concordance correlation coefficient of 0.82 when comparing results from the OCC with results from a DHI laboratory.

Milk somatic cells, factors influencing their release, future prospects, and practical utility in dairy animals: An overview

Milk somatic cells (SCs) are a mixture of milk-producing cells and immune cells. These cells are secreted in milk during the normal course of milking and are used as an index for estimating mammary health and milk quality of dairy animals worldwide. Milk SC is influenced by cow productivity, health, parity, lactation stage, and breed of an animal. Any change in environmental conditions, poor management practices, and also stressful conditions significantly increases the amount of SC coming in milk. Better hygiene and proper nutrition help in reducing milk SC. Milk with low SC means better milk products with a longer shelf life. The present review describes the role of SCs (both secretory and immune) in milk, their role in maintaining the integrity of the mammary gland, and factors affecting their release in milk. This information may help to reduce milk somatic cell counts (SCCs) and to establish differential SCC standards.

Factors affecting milk quality of crossbred dairy cows in automated Herringbone milking system

The aim of the study was to investigate the effect of factors affecting milk quality of crossbred dairy cows milked in automated Herringbone milking system. The study was conducted on 37 crossbred Karan Fries cows of different parities, stages of lactation and udder types for 3 months. The milk quality was assessed based on milk composition, on-line electrical conductivity (EC) and peak conductivity, somatic cell count (SCC) and standard plate count (SPC) of milk samples. The results showed that there was no change in milk composition in terms of fat and SNF except in different parity groups. The milk conductivity was significantly higher in the late stage of lactation. However, no change in SCC values was observed. The udder types showed significant increase in EC values in udders with poor structure and loose attachment. The SCC values were also significantly higher for such udder types. The SPC was significantly higher when the number of milkings on each liner exceeded 2000 milkings/liner. The SCC was had a positive correlation with EC and SPC. The correlation between SPC and SCC was highly significant whereas, EC was moderately correlated with SPC. It can be concluded that the milk quality of crossbred dairy cows was significantly affected by parity, stages of lactation, udder type and liner usage in automated parlours. Therefore, effective management strategy needs to be taken to improve the quality of milk taking into consideration on-line EC, SCC and SPC.

Somatic cell count thresholds in composite and quarter milk samples as indicator of bovine intramammary infection status

The objective of the study was to establish an operational somatic cell count (SCC) threshold to predict the presence of intramammary infection (IMI) in composite milk samples and compare findings with those in quarter milk samples. South African dairy producers now preferred composite milk samples for herd udder health analysis because of increasing cow numbers, convenience of sampling and lower cost. A retrospective study was conducted on 345 461 composite and 89 638 quarter milk samples from South African herds. Variance estimates for the proportion of quarter samples testing positive were adjusted to account for the lack of their independence within individual cows. The IMI at SCC thresholds of 150 000 cells/mL and 200 000 cells/mL differed only by 3.26% in composite milk samples. Youden’s index indicated the optimum SCC thresholds for composite and quarter milk samples as 150 000 cells/mL and 200 000 cells/mL, respectively. At 150 000 cells/mL, sensitivity (95% confidence intervals [CI]) in composite milk samples was 65.3% (64.0%, 66.6%) and specificity was 66.8% (65.7%, 67.9%); and in quarter milk samples, sensitivity at 200 000 cells/mL was 70.8% (69.5%, 72.0%) and specificity was 63.6% (62.4%, 64.8%). The likelihood of infection for udders and quarters, respectively, was 1.034 and 1.327 at an SCC threshold of 150 000 cells/mL and 0.864 cells/mL and 1.177 cells/mL at 200 000 cells/mL. The area under the curve of the receiver operating characteristics graph was 0.7084 and 0.7277 for composite and quarter samples, respectively, indicating that the SCC test could be considered as a good indicator of IMI in both sample types.

Genetic associations for pathogen-specific clinical mastitis and patterns of peaks in somatic cell count

Genetic associations were estimated between pathogen-specific cases of clinical mastitis (CM), lactational average somatic cell score (LACSCS), and patterns of peaks in somatic cell count (SCC) which were based on deviations from the typical lactation curve for SCC. The dataset contained test-day records on SCC in 94 781 lactations of 25 416 cows of different parities. Out of these 94 781 lactations, 41 828 lactations had recordings on occurrence of pathogen-specific CM and on SCC, and 52 953 lactations had recordings on SCC only. A total of 5 324 lactations with cases of CM were recorded. Analysed pathogens were Staphylococcus aureus, coagulase negative staphylococci, Escherichia coli, Streptococcus dysgalactiae, Streptococcus uberis, and culture-negative samples. Pattern definitions were based on three or five consecutive test-day recordings of SCC. They differentiated between short or longer periods of increased SCC, and also between lactations with and without recovery. Occurrence of pathogen-specific CM and presence of patterns of peaks in SCC were both scored as binary traits. Variance components for sire, maternal grandsire, and permanent animal effects were estimated using AS-REML. The estimated heritability for overall CM was 0·04, and similar heritabilities for pathogen-specific CM were estimated. Heritabilities for the patterns of peaks in SCC ranged from 0·01 to 0·06. Heritabilities for LACSCS were 0·07 to 0·08. Genetic correlations with patterns of peaks in SCC differed for each pathogen. Generally, genetic correlations between pathogen-specific CM and patterns of peaks in SCC were stronger than the correlations with LACSCS. This suggests that genetic selection purely on diminishing presence of peaks in SCC would decrease the incidence of pathogen-specific CM more effectively than selecting purely on lower LACSCS.

Evaluation of the Fourier Frequency Spectrum Peaks of Milk Electrical Conductivity Signals as Indexes to Monitor the Dairy Goats' Health Status by On-Line Sensors

The aim of this study is a further characterization of the electrical conductivity (EC) signal of goat milk, acquired on-line by EC sensors, to identify new indexes representative of the EC variations that can be observed during milking, when considering not healthy (NH) glands. Two foremilk gland samples from 42 Saanen goats, were collected for three consecutive weeks and for three different lactation stages (LS: 0–60 Days In Milking (DIM); 61–120 DIM; 121–180 DIM), for a total amount of 1512 samples. Bacteriological analyses and somatic cells counts (SCC) were used to define the health status of the glands. With negative bacteriological analyses and SCC < 1,000,000 cells/mL, glands were classified as healthy. When bacteriological analyses were positive or showed a SCC > 1,000,000 cells/mL, glands were classified as NH. For each milk EC signal, acquired on-line and for each gland considered, the Fourier frequency spectrum of the signal was calculated and three representative frequency peaks were identified. To evaluate data acquired a MIXED procedure was used considering the HS, LS and LS × HS as explanatory variables in the statistical model.Results showed that the studied frequency peaks had a significant relationship with the gland’s health status. Results also explained how the milk EC signals’ pattern change in case of NH glands. In fact, it is characterized by slower fluctuations (due to the lower frequencies of the peaks) and by an irregular trend (due to the higher amplitudes of all the main frequency peaks). Therefore, these frequency peaks could be used as new indexes to improve the performances of algorithms based on multivariate models which evaluate the health status of dairy goats through the use of gland milk EC sensors.

Evaluation of different lactation curve models fitted for milk viscosity recorded by an automated on-line California Mastitis Test

Laboratory somatic cell count (LSCC) records are usually recorded monthly and provide an important information source for breeding and herd management. Daily milk viscosity detection in composite milking (expressed as drain time) with an automated on-line California Mastitis Test (CMT) could serve immediately as an early predictor of udder diseases and might be used as a selection criterion to improve udder health. The aim of the present study was to clarify the relationship between the well-established LSCS and the new trait,'drain time', and to estimate their correlations to important production traits. Data were recorded on the dairy research farm Karkendamm in Germany. Viscosity sensors were installed on every fourth milking stall in the rotary parlour to measure daily drain time records. Weekly LSCC and milk composition data were available. Two data sets were created containing records of 187,692 milkings from 320 cows (D1) and 25,887 drain time records from 311 cows (D2). Different fixed effect models, describing the log-transformed drain time (logDT), were fitted to achieve applicable models for further analysis. Lactation curves were modelled with standard parametric functions (Ali and Schaeffer, Legendre polynomials of second and third degree) of days in milk (DIM). Random regression models were further applied to estimate the correlations between cow effects between logDT and LSCS with further important production traits. LogDT and LSCS were strongest correlated in mid-lactation (r = 0.78). Correlations between logDT and production traits were low to medium. Highest correlations were reached in late lactation between logDT and milk yield (r = -0.31), between logDT and protein content (r = 0.30) and in early as well as in late lactation between logDT and lactose content (r = -0.28). The results of the present study show that the drain time could be used as a new trait for daily mastitis control.

Relationship between milk somatic cell count and postpartum ovarian cyclicity and fertility in dairy cows

The main objective of the study was to describe the relationship of high somatic cell count (SCC) with the incidence of abnormal postpartum resumption of ovarian cyclicity and reproductive performance in dairy cows. The factors influencing SCC were also investigated. Four hundred and forty-seven cows from six dairy herds in Japan were monitored for SCC and postpartum resumption of ovarian cyclicity. Cows with high SCC (200,000 to 500,000) had a higher incidence of prolonged luteal phase (P < 0.01) than cows with an SCC of 50,000 to 100,000. The high SCC cows (> 500,000) also showed a higher incidence of delayed first ovulation post partum than cows with an SCC ≤500,000 (P < 0.05) during the first month post partum. Cows with an SCC of 200,000 to 500,000 showed lower conception and pregnancy rates, and more days from calving to conception than cows with an SCC of less than 200,000 (P < 0.05). Cows in parity 5 or more had a higher incidence of high SCC than cows in the first and second parities (P < 0.05). It is concluded that cows with a high SCC have a higher incidence of abnormal postpartum resumption of ovarian cyclicity, leading to reduced reproductive performance.

A novel method of analyzing daily milk production and electrical conductivity to predict disease onset

This study evaluates the changes in milk production (yield; MY) and milk electrical conductivity (MEC) before and after disease diagnosis and proposes a cow health monitoring scheme based on observing individual daily MY and MEC. All reproductive and health events were recorded on occurrence, and MY and MEC were collected at each milking from January 2004 through November 2006 for 587 cows. The first 24 mo (January 2004 until December 2005) were used to investigate the effects of disease on MY and MEC, model MY and MEC of healthy animals, and develop a health monitoring scheme to detect disease based on changes in a cow's MY or MEC. The remaining 11 mo of data (January to November 2006) were used to compare the performance of the health monitoring schemes developed in this study to the disease detection system currently used on the farm. Mixed model was used to examine the effect of diseases on MY and MEC. Days in milk (DIM), DIM x DIM, and ambient temperature were entered as quantitative variables and number of calves, parity, calving difficulty, day relative to breeding, day of somatotropin treatment, and 25 health event categories were entered as categorical variables. Significant changes in MY and MEC were observed as early as 10 and 9 d before diagnosis. Greatest cumulative effect on MY over the 59-d evaluation period was estimated for miscellaneous digestive disorders (mainly diarrhea) and udder scald, at -304.42 and -304.17 kg, respectively. The greatest average daily effect was estimated for milk fever with a 10.36-kg decrease in MY and 8.3% increase in MEC. Milk yield and MEC was modeled by an autoregressive model using a subset of healthy cow records. Six different self-starting cumulative sum and Shewhart charting schemes were designed using 3 different specificities (98, 99, and 99.5%) and based on MY alone or MY and MEC. Monitoring schemes developed in this study issue alerts earlier relative to the day of diagnosis of udder, reproductive, or metabolic problems, are more sensitive, and give fewer false-positive alerts than the disease detection system currently used on the farm.

Relationship between somatic cell count and milk yield in different stages of lactation

The association between somatic cell count (SCC) and daily milk yield in different stages of lactation was investigated in cows free of clinical mastitis (CM). Data were recorded between 1989 and 2004 in a research herd, and consisted of weekly test-day (TD) records from 1,155 lactations of Swedish Holstein and Swedish Red cows. The main data set (data set A) containing 36,117 records excluded TD affected by CM. In this data set, the geometric mean SCC was 55,000 and 95,000 cells/mL in primiparous and multiparous cows, respectively. A subset of data set A (data set B), containing 27,753 records excluding all TD sampled in lactations affected by CM, was created to investigate the effect of subclinical mastitis (SCM) in lactations free of CM. Daily milk yields were analyzed using a mixed linear model with lactation stage; linear, quadratic and cubic regressions of log(2)-transformed and centered SCC nested within lactation stage; weeks in lactation; TD season; parity; breed; pregnancy status; year-season of calving; calving, reproductive, metabolic and claw disorders; and housing system as fixed effects. A random regression was included to further improve the modeling of the lactation curve. Primiparous and multiparous cows were analyzed separately. The magnitude of daily milk loss associated with increased SCC depended on stage of lactation and parity, and was most extensive in late lactation irrespective of parity. In data set A, daily milk loss at an SCC of 500,000 cells/mL ranged from 0.7 to 2.0 kg (3 to 9%) in primiparous cows, depending on stage of lactation. In multiparous cows, corresponding loss was 1.1 to 3.7 kg (4 to 18%). Regression coefficients of primiparous cows estimated from data set B were consistent with those obtained from data set A, whereas data set B generated more negative regression coefficients of multiparous cows suggesting a higher milk loss associated with increased SCC in lactations in which the cow did not develop CM. The 305-d milk loss in the average lactation affected with SCM was 155 kg of milk (2%) in primiparous cows and 445 kg of milk (5%) in multiparous cows. It was concluded that multiparous cows in late lactation can be expected to be responsible for the majority of the herd-level production loss caused by SCM, and that preventive measures need to focus on reducing the incidence of SCM in such cows.

Associations between defensin polymorphism and somatic cell count in milk and milk utility traits in Jersey dairy cows

The aim of the study was to investigate associations between combined defensin genotypes (CDGs) and somatic cell count (SCC) in Jersey cows. The study included a herd of 184 dairy Jersey cows from Wielkopolska region in Poland. Polymerase chain reaction-restriction fragment length polymorphism analysis with TaqI restrictase established the existence of 12 CDGs with a frequency of over 1%. The most frequent were A1A2B1B2C1C2 and A1A2B1B2C1- genotypes with a frequency of 56.9783% and 12.5% respectively. The study also confirmed the existence of a statistically significant association between SCC and the year of study, season, lactation stage and cow. The highest SCC (transformed into a logarithmic scale) was found in the milk of cows with A1-B1-C1C2 genotype, whereas the lowest one in cows with A2-B1B2C1C2 genotype. Another aim of the project was to study the association between CDG and milk production traits, such as daily milk yield and fat and protein content. CDG was found to be a significant factor affecting daily milk yield and non-significant for fat and protein content. The highest daily milk yield was observed in cows with CDGs A1A2B1B2C2- and -A2-B1B2C1-, whereas the lowest one was characteristic of -A2-B1-C1C2 and A1A2B1-C1- animals. Fat content was found to be related to CDG genotype in the opposite way; the highest values were recorded in animals with -A2-B1B2C1- genotype, the lowest - in animals with -A2-B1-C1C2 genotype. Similar results were observed in protein content in milk -A2-B1B2C1-, the highest content and -A2-B1-C1C2, the lowest content. The results confirm the hypothesis of using CDG as an SCC marker. However, further studies should be conducted to confirm these results before CDG can be used as a marker in a mass selection of dairy cows.

Apical electrolyte concentration modulates barrier function and tight junction protein localization in bovine mammary epithelium

In vitro mammary epithelial cell models typically fail to form a consistently tight barrier that can effectively separate blood from milk. Our hypothesis was that mammary epithelial barrier function would be affected by changes in luminal ion concentration and inflammatory cytokines. Bovine mammary epithelial (BME-UV cell line) cells were grown to confluence on permeable supports with a standard basolateral medium and either high-electrolyte (H-elec) or low-electrolyte (L-elec) apical medium for 14 days. Apical media were changed to/from H-elec medium at predetermined times prior to assay. Transepithelial electrical resistance ( Rte) was highest in monolayers continuously exposed to apical L-elec. A time-dependent decline in Rtebegan within 24 h of H-elec medium exposure. Change from H-elec medium to L-elec medium time-dependently increased Rte. Permeation by FITC-conjugated dextran was elevated across monolayers exposed to H-elec, suggesting compromise of a paracellular pathway. Significant alteration in occludin distribution was evident, concomitant with the changes in Rte, although total occludin was unchanged. Neither substitution of Na+with N-methyl-d-glucosamine (NMDG+) nor pharmacological inhibition of transcellular Na+transport pathways abrogated the effects of apical H-elec medium on Rte. Tumor necrosis factor alpha, but not interleukin-1β nor interleukin-6, in the apical compartment caused a significant decrease in Rtewithin 8 h. These results indicate that mammary epithelium is a dynamic barrier whose cell-cell contacts are acutely modulated by cytokines and luminal electrolyte environment. Results not only demonstrate that BME-UV cells are a model system representative of mammary epithelium but also provide critical information that can be applied to other mammary model systems to improve their physiological relevance.

Acute phase protein concentrations in serum and milk from healthy cows, cows with clinical mastitis and cows with extramammary inflammatory conditions

The concentrations of the two acute phase proteins, serum amyloid A and haptoglobin, in serum and milk were compared in 10 cows with clinical mastitis, 11 cows with extramammary inflammatory conditions and 10 clinically healthy control cows. The concentrations of both acute phase proteins were higher in the serum and milk of the cows with mastitis than in the cows in the other two groups. Four of the cows with extramammary inflammatory conditions had serum amyloid A concentrations in serum above 100 microg/ml, but negligible concentrations in milk, indicating that a pathogen must be present in the mammary gland for serum amyloid A to accumulate in milk. The acute phase protein concentrations in milk increased significantly with increasing somatic cell count, suggesting that they may be indicators of the severity of an infection.

Potential for improving description of bovine udder health status by combined analysis of milk parameters

The objective of this study was to assess the potential of a stepwise multivariate procedure to quantify cow-level udder health based on eight milk parameters: milk yield, protein percentage, fat percentage, lactose percentage, citrate percentage, somatic cell count (SCC), and two electrical conductivity parameters. The data were collected in one research herd and included 821 cow-level observations. In addition to milk parameters, disease recordings and bacteriology on quarter milk samples every eighth week throughout lactation were included. A multivariate mixed model was applied to the milk parameters in a healthy subset to adjust for the following systematic factors: total mixed ration (TMR) energy density, breed-line combination, parity, stage of lactation, and season. The proportion of variance accounted for by the mixed model ranged from 0.14 to 0.82 depending on milk parameter. The adjustments estimated in the healthy subset were applied to the whole dataset, including observations pertaining to nonhealthy cows. Combined description of the adjusted variation in the milk parameters was performed with a principal component analysis. The first principal component (Prin1) described 30% of the adjusted variation and was interpreted as being the main consequences of mastitis. Finally, cluster analysis based on Prin1 separated the observations into nine clusters, which were strongly associated with udder health in terms of increasing clinical and subclinical mastitis with increasing level of Prin1. It was concluded that a multivariate approach to assess udder health from milk parameters has the potential to substantially improve description of udder health.

Evaluation of measurements of the conductivity of quarter milk samples for the early diagnosis of mastitis

Measurements of the conductivity of quarter milk samples were made in 31 cows in a 70-cow herd in southeast England, for a period of 15 weeks. Over this period, 42 per cent of cow-weeks and 20 per cent of quarter-weeks had an increase in quarter milk conductivity of 10 per cent of more compared with the mean conductivity of the previous 14 milkings. Fourteen per cent of quarter-weeks had an increase in conductivity of 15 per cent or more. The geometric mean somatic cell count (cell count) was higher in quarter-weeks with a 10 per cent or greater increase in conductivity than in quarter-weeks with a conductivity change of less than 10 per cent. At a conductivity threshold of 10 or 15 per cent and a cell count threshold of 200,000 or 400,000 cells/ml the specificity of this system was estimated to be 85 to 92 per cent, the sensitivity 40 to 54 per cent, the negative predictive value 87 to 93 per cent and the positive predictive value 33 to 55 per cent. The positive predictive value of the individual quarter milk conductivity was insufficiently accurate to be used as the sole criterion for the selection of quarters for early antibiotic treatment.

The effect of pathogen-specific clinical mastitis on the lactation curve for somatic cell count

Data from 274 Dutch herds recording clinical mastitis (CM) over an 18-mo period were used to investigate the effect of pathogen-specific CM on the lactation curve for somatic cell count (SCC). Analyzed pathogens were Staphylococcus aureus, coagulase-negative staphylococci, Escherichia coli, Streptococcus dysgalactiae, Streptococcus uberis, other streptococci, and the culture-negative samples. The dataset contained 178,754 test-day records on SCC, recorded in 26,411 lactations of 21,525 cows of different parities. In lactations without both clinical and subclinical mastitis, SCC was high shortly after parturition, decreased to a minimum at 50 days in milk (DIM), and increased slowly toward the end of the lactation. Effects of CM on lactation curves for SCC differed among the pathogens isolated. Before a case of clinical E. coli mastitis occurred, SCC was close to the SCC of lactations without both clinical and subclinical mastitis, and after the case of CM had occurred, SCC returned rather quickly to a low level again. Similar curves were found for lactations with cases of CM associated with culture-negative samples. Before a case of clinical Staph. aureus mastitis occurred, average SCC was already high, and it remained high after the occurrence. Effects of CM associated with Strep. dysgalactiae, Strep. uberis, and other streptococci on the lactation curve for SCC were comparable. They showed a continuous increase in SCC until the case of pathogen-specific CM occurred, and afterwards SCC stayed at a higher level. Using SCC test-day records, these typical characteristics of each pathogen may be used to find more effective indicators of CM.

Monitoring nonlactating cow intramammary infection dynamics using DHI somatic cell count data

Although the nonlactating period presents a risk for intramammary infection, efficient systems to monitor infection status of recently calved cows have not been developed, and benchmarks for interpretation have not been established. Individual cow somatic cell count (SCC) data for the current and previous six monthly Dairy Herd Improvement milk tests and the last SCC of the previous lactation and first SCC of the current lactation were summarized for all milking cows in a selection of Wisconsin dairy herds. Prevalence of infection, herd new infection rate, fresh cow contribution to herd new infection rate, dry cow new infection rate, heifer new infection rate, and dry cow cure rate were estimated using a threshold of 200,000/ml. In 145 herds, mean (range) heifer new infection rate was 21.3% (0 to 58%). The cut-point for the 10th percentile of herds was 8%. Mean (range) dry cow new infection rate in cows that were uninfected at the last test before dry off was 22.4% (0 to 71%), and the cut-point for the 10th percentile of herds was 9%. Although nonlactating cow and heifer new infection rates increased with weighted 6-mo mean herd SCC, the between-herd variation was large, suggesting that on-farm factors are important in determining the rates of infection. In a subset of 51 Wisconsin dairy herds, significant monthly variation in weighted SCC, prevalence, herd new infection rate, and fresh cow contribution to herd new infection rate were detected. Elevations in SCC and prevalence of infection during the summer (July through September) were associated with significant increases in fresh cow and herd new infection rates.

Sensitivity and specificity of somatic cell count and California Mastitis Test for identifying intramammary infection in early lactation

Associations between values for the somatic cell count (SCC) or the California Mastitis Test (CMT) and intramammary infection (IMI) were studied in 131 dairy cows from three herds during the first 10 d post-calving. Intramammary infection was defined as the presence of one or two bacterial species in one or both quarter milk samples taken within 12 h of calving and at d 3 postcalving. Quarter milk samples identified IMI in 36% of glands. Values for SCC declined at a significantly faster rate over the first 10 d postcalving in non-infected quarters than in infected quarters. The usefulness of quarter milk SCC and CMT for screening was evaluated by calculating the sensitivity and specificity for various threshold values and days postcalving. A SCC threshold of 100,000 cells/ml for quarter samples evaluated on d 5 postcalving had the maximal sensitivity and specificity for detecting IMI. Evaluation of the CMT samples taken on d 3 postcalving using a threshold reaction of greater than zero had the highest sensitivity and specificity for detecting IMI. With this CMT sampling scheme, the sensitivities for detecting IMI with any pathogen, IMI with a major pathogen, and IMI with a minor pathogen were 56.7, 66.7, and 49.5, respectively. The CMT could have a useful role in dairy herd monitoring programs as a screening test to detect fresh cows with IMI caused by major pathogens.

Milk yield and composition, nutrition, body conformation traits, body condition scores, fertility and diseases in high-yielding dairy cows--Part 1

Twenty-nine pairs of high-yielding dairy cows (HC; > or = 45 kg/day reached at least once during lactation) and corresponding control cows (CC; with milk yields representing the average yield of the herds) were examined on 29 Swiss farms from March 1995 to September 1996. The hypotheses were tested that there are differences in feed intake, body-conformation traits, body weight (BW), body condition score (BCS), fertility status and disease incidence between HC and CC cows. Cows were studied 2 weeks before and at 5, 9, 13, 17 and 40 weeks post-partum. HC cows produced more energy-corrected milk (ECM) than CC cows (10,670 +/- 321 kg in 293 +/- 5 days and 8385 +/- 283 kg in 294 +/- 4 days, respectively; P < or = 0.001) and yields in the first 100 days of lactation were greater in HC than in CC cows (46.2 +/- 1.1 and 36.2 +/- 1.0 kg ECM/day, respectively; P < or = 0.001). Concentrate intake was greater (P < or = 0.05) in HC than in CC cows (7.6 +/- 0.5 and 5.7 +/- 0.5 kg/day, respectively) and dry matter intakes (measured in week 5 of lactation over 3 days on six farms) were greater in HC than in CC cows (24.0 +/- 1.1 and 20.3 +/- 1.1 kg/day, respectively; P < or = 0.001). HC cows were taller than CC cows (wither heights 143.3 +/- 0.8 and 140.1 +/- 0.8 cm, respectively; P < or = 0.01). Although BW in HC cows was greater than in CC cows throughout the study, differences and decreases of BW during lactation were not significant. BCS at the end of pregnancy and decrements during lactation were similar in HC and CC cows. Fertility parameters were similar in HC and CC cows. Incidences of mastitis, claw and feet problems, hypocalcemia/downer cow syndrome, ovarian cysts and abortions were similar in HC and CC cows, but there were more indigestion problems in HC than in CC cows.

Immune surveillance of mammary tissue by phagocytic cells

The leukocytes in milk consist of lymphocytes, neutrophil polymorphonuclear leukocytes (PMN) and macrophages. Lymphocytes together with antigen-presenting cells function in the generation of an effective immune response. Lymphocytes can be divided into two distinct subsets, T- and B-lymphocytes, that differ in function and protein products. The professional phagocytic cells of the bovine mammary gland are PMN and macrophages. In the normal mammary gland macrophages are the predominate cells which act as sentinels to invading mastitis causing pathogens. Once the invaders are detected, macrophages release chemical messengers called chemoattractants that cause the directed migration of PMN into the infection. Migration of neutrophils into mammary tissue provides the first immunological line of defense against bacteria that penetrate the physical barrier of the teat canal. However, their presence is like a double-edged sword. While the PMN are phagocytosing and destroying the invading pathogens, they inadvertently release chemicals which induces swelling of secretory epithelium cytoplasm, sloughing of secretory cells, and decreased secretory activity. Permanent scarring will result in a loss of milk production. Resident and newly migrated macrophages help reduce the damage to the epithelium by phagocytosing PMN that undergo programmed cell death through a process called apoptosis. Specific ligands on the neutrophil surface are required for directed migration and phagocytosis. In response to infection, freshly migrated leukocytes express greater numbers of cell surface receptors for immunoglobulins and complement and are more phagocytic than their counterparts in blood. However, phagocytic activity rapidly decreases with continued exposure to inhibitory factors such as milk fat globules and casein in mammary secretions. Compensatory hypertrophy in non-mastitic quarters partially compensates for lost milk production in diseased quarters. Advances in molecular biology are making available the tools, techniques, and products to study and modulate host-parasite interactions. For example the cloning and expression of proteins that bind endotoxin may provide ways of reducing damaging effects of endotoxin during acute coliform mastitis. The successful formation of bifunctional monoclonal antibodies for the targeted lysis of mastitis causing bacteria represents a new line of therapeutics for the control of mastitis in dairy cows.

Quarter-milk somatic cell count at calving and at the first six milkings after calving

Thirty cows were studied during the first six milkings after calving. Quarter foremilk samples were collected by the farmers at calving and at six subsequent milkings. Geometric-mean somatic cell count (SCC) decreased from 593,000 at calving to 126,000 cells/ml at the sixth milking after calving. In quarters infected with major pathogenic bacteria, geometric-mean SCC was 3,229,000 cells/ml at calving, and 1,257,000 cells/ml at the sixth milking after calving. In quarters infected with minor pathogenic bacteria, geometric-mean SCC was 1,000,000 cells/ml at calving, and 170,000 cells/ml at the sixth milking after calving. In culture-negative quarters, geometric-mean SCC decreased from 306,000 at calving to 42,000 cells/ml at the sixth milking after calving. Quarter SCC can be used early postpartum to give an indication of intra-mammary infection status.

Selecting linear-score distributions for modelling milk-culture results

The data for this cross-sectional retrospective study are from surveys of 65 dairy-cattle herds in central New York, USA sampled between February, 1993 and March, 1995. The objective was to identify probability distributions of logarithmically transformed somatic-cell counts (linear score) for use in a simulation model of mastitis and milk quality. Probability density functions were estimated using maximum-likelihood estimators for the linear score of individual-cow composite-milk samples culture negative and culture positive for the pathogens Streptococcus agalactiae, Streptococcus non-agalactiae, Staphylococcus aureus, and coagulase-negative staphylococci for the complete dataset and by bulk-tank somatic-cell count group (< 500,000, > or = 500,000 SCC/ml). Based on the rankings of three goodness-of-fit tests (Anderson-Darling, Kolmogorov-Smirnov and chi 2), the Weibull distribution (among the three top-ranking distributions for 14 out of 15 cases) may be used to model the individual-cow linear-score response by culture-result-specific bulk-tank somatic-cell count group. A beta distribution was among the three top-ranking distributions for nine out of 15 culture-result-specific bulk-tank somatic-cell count groups and has a logical relationship to linear score because it is defined on a fixed interval. On the other hand, the normal distribution had a poorer fit than the Weibull and at least two other distributions for all culture negative and coagulase-negative staphylococci samples. We do not assume that the underlying biological processes are fully explained by either Weibull or beta distribution--but modelling the linear score for the above culture results with these distributions provided an adequate fit to the survey data, reduced the need for two-sided truncation that open intervals needed, and had errors that did not appear to be systematically positive or negative.

Influence of parity and stage of lactation on the somatic cell count in bacteriologically negative dairy cows

This study examines the influence of parity, stage of lactation, and single isolations (i.e., the isolation of a microorganism that could not be reisolated in the same quarter in the next sampling) of staphylococci other than Staphylococcus aureus (coagulase-negative staphylococci), Corynebacterium bovis, or esculin-positive cocci other than Streptococcus uberis (referred to as esculin-positive cocci throughout) on the monthly log(e)-transformed somatic cell count (SCC) for 180 first, second, and third parity cows that were observed over a whole lactation. Repeated measures ANOVA was used to analyze the data. No significant effect was found for the infection variable. However, the results indicated that even single isolations of coagulase-negative staphylocci, C. bovis, or esculin-positive cocci resulted in a numerical or statistically significant increase in SCC. Least squares mean SCC (log(e)-transformed) for bacterio-logically negative cows and cows with single isolations of coagulase-negative staphylococci, C. bovis, or esculin-positive cocci were 3.90, 3.97, 4.08, and 4.17, respectively. Significant effects of parity, stage of lactation, and the interaction of parity and stage of lactation could not be found when only bacteriologically negative cows were considered. Least squares mean SCC for first, second, and third parity cows were 3.80, 3.93, and 3.97, respectively. However, the effects of parity, stage of lactation, and the interaction of parity and stage of lactation were significant when all 180 cows were included. Therefore, these effects must be due to factors that were present in the infected groups.

Relationship between somatic cell count and intramammary infection of the half udder in dairy ewes

A total of 1382 milk samples from half udders of three breeds of ewes (686 Assaf, 422 Churra, and 274 Castellana) were collected aseptically at midlactation from 18 flocks in the Castile-León region of Spain. Bacteriological tests were carried out on the samples to ascertain the status and type of IMI. Somatic cell counts were determined for all samples after bacteriological analysis. Analysis of variance showed significant effects of breed, IMI status, flock nested within breed by milking type, organism within IMI status, and interactions of breed by milking type and of breed by organism. The most frequent bacterial groups were staphylococci, especially coagulase-negative staphylococci, followed by streptococci, micrococci, and yeasts. The SCC response was related to the bacterial group involved in the IMI; coagulase-negative staphylococci showed significantly lower SCC values than those for coagulase-positive staphylococci and streptococci. Highest percentages of IMI by major pathogens and highest SCC, both in the absence of IMI and in staphylococcal IMI, were in Assaf ewes. The threshold of 300,000 cells/ml allowed 81% of the half udders to be correctly classified according to IMI status. However, the existence of breed differences in SCC response and IMI type could make the use of specific SCC thresholds for each breed advisable.

Physiology of mastitis and factors affecting somatic cell counts

Inflammation of the mammary gland that results from the introduction and multiplication of pathogenic microorganisms in the mammary gland is a complex series of events leading to reduced synthetic activity, compositional changes, and elevated SCC. The magnitude and temporal relationships of these responses vary with nutritional status, other animal factors, and the pathogen involved. Because the elevation of SCC is a response to an insult to the mammary gland and is modulated by inflammatory mediators, the major factor influencing SCC is infection status. The effects of stage of lactation, age, season, and various stresses on SCC are minor if the gland is uninfected. Except for normal diurnal variation, few factors other than infection status have a significant impact on milk SCC.

Role of the neutrophil leucocyte in the local and systemic reactions during experimentally induced E. coli mastitis in cows immediately after calving

Mammary leucocytes are the major contributors to natural defence against mastitis after a microorganism has entered the gland. This paper reviews the role of the neutrophil granulocyte during acute coliform mastitis in cows in the periparturient period. Qualitative and quantitative aspects of several neutrophil cell functions before and during experimentally induced infections are briefly discussed.

Relations between on-line electrical conductivity and daily milk production on a low somatic cell count farm

To study the relation between on-line electrical conductivity and daily milk production, data of 1389 cow days were analyzed. After correction for cow effects and DIM, a rise of 1 mS of the mean electrical conductivity caused a decline of .88 kg/d in milk production. A rise of 1 ln(SCC) unit was associated with an additional decline of .54 kg/d in milk production. In cows without clinical mastitis during the test period, the losses associated with mean electrical conductivity and ln(SCC) were 1.06 and .45 kg/d of milk production, respectively. Electrical conductivity and SCC were associated with daily production loss; the effects were additive. Therefore, electrical conductivity and SCC can be utilized as indirect tests of subclinical mastitis.

Electrical conductivity of milk: measurement, modifiers, and meta analysis of mastitis detection performance

The physics, physiology, and pathology of electrical conductivity of milk are described. Based on a meta analysis, the use of electrical conductivity as a mastitis detection tool is discussed. Most reports were based on subclinical mastitis data. The gold standards of the different reports are discussed. With an overall sensitivity of 66% and an overall specificity of 94%, the predictive value of a positive electrical conductivity test remains low in a low prevalence population. The use of on-line systems for clinical mastitis detection is discussed. On-line systems that combine multiple data and perform multifactorial analyses will be of interest to the dairy industry.

Analysis of somatic cell count data by a peak evaluation algorithm to determine inflammation events

Increases in SCC are an expression of inflammation events in the udder. Inflammation events are sporadic, of variable amplitude and duration, and can be analyzed by computer programs designed to evaluate pulses of hormone secretion. Baseline values for SCC, which take into account long-term trends, were calculated using the PULSAR peak evaluation algorithm. An inflammation event was defined as an increase of log2(SCC) of at least 1 unit from the preceding data point if the observed value exceeded the baseline value by a threshold value. Incidence rate, duration, and amplitude of inflammation events were calculated. Weekly composite milk SCC from individual cows from two Florida dairy farms were recorded. Data were analyzed for effects of season (summer and fall) and bST in two separate data sets. Incidence rate of inflammation events was higher in summer than in fall (4.31 and 2.91 events per cow x year). In one of two data sets only, duration of inflammation events was longer in cows treated with bST (2.4 +/- .2 vs. 1.6 +/- .2 wk). In contrast, least squares analysis of variance of log2(SCC) did not detect differences due to season or bST. The use of the peak evaluation algorithm led to the detection of seasonal and bST effects on inflammation events in cows.

Effects of systematic influences and intramammary infection on differential and total somatic cell counts in quarter milk samples from dairy cows

Effects of bacteriological status, stage of lactation, parity and season of sampling on differential and total somatic cell counts were estimated in quarter milk samples taken from 39 dairy cows. Log somatic cell count was affected by the bacteriological status of the quarter, as well as by the bacteriological status of adjacent quarters. Differential cell counts were affected by presence or absence of pathogens in the quarters themselves, but not by the bacteriological status of the adjacent quarters. Log somatic cell count was clearly affected by stage of lactation, due mainly to physiological variation, but possibly also accentuated by variation in infection rates throughout lactation. With the exception of early lactation, little physiological variation throughout lactation was detected for differential cell counts. Presence of infections seemed to have some indirect effect on trends throughout lactation as regards percentages of granulocytes and monocytes. Variation in somatic cell counts due to parity could be explained by variation in infection rates, rather than being physiologically determined.